The Maintenance Challenge UK and EU's Rail Cannot Ignore

Network

The Maintenance Challenge UK and EU's Rail Cannot Ignore

A “railway fit for the future”: the EU and the UK have used the same phrase to describe their ambitions for rail, and the same shorthand captures the scale of the challenge. Both face the task of funding major upgrades, transforming ageing infrastructure and complex governance structures, all while keeping trains running as the network is rebuilt around them.

In the EU, those ambitions are anchored in the Trans-European Transport Network (TEN-T) regulation: a commitment to tripling high-speed rail traffic by 2050, underpinned by phased infrastructure obligations across a network of some 138,000 kilometres of railway.

The UK’s ambitions are no less significant. The creation of Great British Railways, a new public body that will bring responsibility for both track and train under a single roof for the first time since privatisation, represents one of the most consequential structural reforms in a generation. The intention is to end the fragmentation that has long characterised British rail: separate operators, separate incentives and infrastructure managed at one remove from the services that depend on it.

The asset management gap

Across both contexts, one dimension of this ambition remains underexplored: maintenance. While the challenges of new infrastructure investment are well documented, the asset management foundations required to sustain expanded, higher-performing networks are largely underdeveloped.

In addition, governments and infrastructure managers across Europe are meeting this moment with strained finances, at a time when the costs of maintaining and renewing the continent’s rail infrastructure already run to more than €25 billion a year, a figure forecast to rise steeply as networks expand and service demands grow.

However, the challenge facing infrastructure operators is not simply one of resources. It reflects the depth and complexity of managing a broad diversity of systems (track, signalling, electrification, maintenance equipment) across networks of thousands of kilometres, in the context of staff shortages and constrained budgets.

The core challenge is not just fixing what breaks: it is knowing what will break, when, and what the operational consequence of waiting actually costs. That requires a clear-eyed assessment of whether preservation, repair, replacement or upgrading is the right response, and that judgement depends on good data.

A matter of disjointed systems

But data is precisely where the foundations are often weakest. Inspection records sit in one platform, work orders in another, asset registers in a third and financial data somewhere else again. A common thread, from the 2020 Stonehaven derailment in Scotland to the 2023 Tempi collision in Greece, is identified vulnerabilities sitting inside the system for years, through delayed upgrades, incomplete inspections, fragmented responsibility and slow corrective action.

The operational consequences of this fragmentation extend beyond safety. Research by BCG has shown that, while maintenance accounts for 30% to 40% of operational expenses across European rail infrastructure operators, prioritisation often follows inconsistent and ad hoc processes. Limited data accuracy and inadequate asset management systems force a reactive posture that disrupts service and raises costs. The result is a familiar spiral: rising network demands lead to rising maintenance costs, which lead to underinvestment, which leads to more failures and higher reactive expenditure.

In the UK, the promise of Great British Railways is partly that structural integration, aligning incentives between track and train, will help break that spiral. But structural reform alone is not sufficient. The data and operational foundations have to be built alongside it, or the new institution will simply inherit the same fragmented information landscape in a new organisational wrapper.

This matters for ERTMS deployment too. Rolling out European train control technology across a legacy network is not purely a signalling project: it changes the data environment fundamentally, creating new streams of operational information that infrastructure managers will need to integrate into their maintenance and planning processes. Countries that are further ahead, including Switzerland, the Netherlands and Denmark, have found that the benefits of ERTMS compound when the underlying asset management systems are ready to absorb and use that data. Where those systems are immature, the technology’s potential goes unrealised.

Getting the foundations right

What has shifted in recent years is both the availability of tools to address these challenges and the impossibility of ignoring the cost of inaction. Infrastructure managers that increase the maturity of their maintenance processes, reducing manual workloads, improving workforce planning and extending asset lifetimes, can achieve productivity gains of up to 20% whilst improving operational stability by up to 15%.

Those gains depend on getting the foundations right first: a consolidated asset register, standardised processes, and data that flows between inspection, planning and execution rather than sitting in disconnected silos.

The most instructive examples come from operators managing Europe’s most demanding networks. At the centre of their maintenance operation is typically an enterprise asset management (EAM) platform linking every physical asset to its maintenance history, intervention schedule and cost record.

The critical development of the past decade is not the EAM platform itself but its integration with geospatial intelligence. Linear infrastructure like rail does not fit neatly into traditional asset registers built around discrete objects. A track section, a tunnel lining or an electrification catenary are assets defined by location and continuity, not by serial number. GIS-based linear asset management, integrated with EAM, allows maintenance teams to manage work orders tied to specific track segments, plan interventions against possession windows (the authorised downtime slots when maintenance can actually occur) and maintain a complete spatial picture of network condition at any moment.

APM: unifying process data, risks, costs and actions

An approach that yields particular dividends is asset performance management (APM). Over the past decade, operators have sought to move from reactive to predictive and prescriptive maintenance, a progression that reduces costs, but only if maintenance frequencies are calibrated correctly. Over-maintaining is wasteful; under-maintaining is dangerous. The “sweet spot” is where preventive maintenance costs and breakdown costs intersect at their minimum combined total.

Reaching that sweet spot requires integrating dimensions that typically sit in different systems: failure modes, asset criticality and costs, operational context, and a feedback loop that ensures findings feed back into maintenance interventions. That is precisely what APM does.

An APM platform layers on top of existing EAM and ERP systems, integrating process historians to access continuous sensor data: axle counter data, vibration sensors on switches and crossings, catenary tension monitoring, power supply monitoring on electrified lines and track circuit data from signalling systems. In doing so, it unifies the process layer, the analysis, the cost dimension and the decision layer, triggering work orders based on evidence rather than schedule or intuition.

The truth is in the field

These tools need a solid connection to field operations to deliver their value. Mobile solutions that give technicians access to work orders, asset records and inspection forms in the field, including offline capability in tunnels and remote sections, are essential for closing the loop between the physical network and the data systems that model it.

transN, a Swiss operator running both rail and road services, illustrates how this works in practice. Relying on an integrated EAM platform and a mobile offline application, field technicians access work orders and electronic checklists in real time, feeding a centralised record of corrective and preventive maintenance. The transition has also significantly reduced reliance on paper and spreadsheets. Every intervention recorded in the field becomes an input to the asset history, and that history becomes the raw material for predictive analysis.

Sensor technologies add a further layer of real-time awareness. LiDAR-based monitoring can detect unauthorised intrusions, objects on track and structural deformations with centimetre-level accuracy, regardless of lighting or weather. Integrated with control systems, these capabilities can trigger automatic train slowdowns, alert operations centres and create timestamped event records without relying on human observation.

A central matter for network performance

A solid technology foundation also changes the relationship between infrastructure managers and the long-term stewardship of the network. Operators with mature asset management capabilities can advise not just on what needs fixing today, but on what the replacement lifecycle looks like over a 25-year horizon, turning maintenance data into capital planning intelligence.

As network expansion continues and the €25 billion annual maintenance cost base grows, the pressure to extract more performance from existing infrastructure before it needs full replacement will only intensify. A network maintained intelligently, with the right combination of sensor data, geospatial intelligence and predictive analytics, can defer capital expenditure, reduce emergency interventions and sustain high availability. The gap between operators who have built those foundations and those who have not is becoming the gap between a network that performs and one that does not.